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We introduce a formalism for computing bond percolation properties of a class of correlated and clustered random graphs. This class of graphs is a generalization of the Configuration Model where nodes of different types are connected via…

Statistical Mechanics · Physics 2017-10-06 Antoine Allard , Laurent Hébert-Dufresne , Pierre-André Noël , Vincent Marceau , Louis J. Dubé

A growing random graph is constructed by successively sampling without replacement an element from the pool of virtual vertices and edges. At start of the process the pool contains $N$ virtual vertices and no edges. Each time a vertex is…

Probability · Mathematics 2024-02-29 Michael Farber , Alexander Gnedin , Wajid Mannan

We investigate structural properties of large, sparse random graphs through the lens of "sampling convergence" (Borgs et. al. (2017)). Sampling convergence generalizes left convergence to sparse graphs, and describes the limit in terms of a…

Probability · Mathematics 2019-07-04 Christian Borgs , Jennifer T. Chayes , Souvik Dhara , Subhabrata Sen

Finding the common structural brain connectivity network for a given population is an open problem, crucial for current neuro-science. Recent evidence suggests there's a tightly connected network shared between humans. Obtaining this…

Neurons and Cognition · Quantitative Biology 2017-01-10 Nahuel Lascano , Guillermo Gallardo , Rachid Deriche , Dorian Mazauric , Demian Wassermann

We study normal approximation of subgraph counts in a model of spatial scale-free random networks known as the age-dependent random connection model. In the light-tailed regime where only moments of order $(2 + \varepsilon)$ are finite, we…

Probability · Mathematics 2025-05-15 Christian Hirsch , Raphaël Lachièze-Rey , Takashi Owada

Tensor network contraction is central to problems ranging from many-body physics to computer science. We describe how to approximate tensor network contraction through bond compression on arbitrary graphs. In particular, we introduce a…

Quantum Physics · Physics 2024-01-30 Johnnie Gray , Garnet Kin-Lic Chan

The configuration model is the most natural model to generate a random multigraph with a given degree sequence. We use the notion of dense graph limits to characterize the special form of limit objects of convergent sequences of…

Probability · Mathematics 2012-04-11 Balazs Rath , Laszlo Szakacs

Given a graph $G$, viewed as a loop-less symmetric digraph, we study the maximum number of fixed points in a conjunctive boolean network with $G$ as interaction graph. We prove that if $G$ has no induced $C_4$, then this quantity equals…

Combinatorics · Mathematics 2017-11-08 Julio Aracena , Adrien Richard , Lilian Salinas

A wireless communication network is considered where any two nodes are connected if the signal-to-interference ratio (SIR) between them is greater than a threshold. Assuming that the nodes of the wireless network are distributed as a…

Information Theory · Computer Science 2016-11-17 Rahul Vaze

We study the asymptotic distributions of the number of crossings and the number of simple chords in a random chord diagram. Using size-bias coupling and Stein's method, we obtain bounds on the Kolmogorov distance between the distribution of…

Probability · Mathematics 2023-01-13 J. E. Paguyo

We introduce and develop a theory of limits for sequences of sparse graphs based on $L^p$ graphons, which generalizes both the existing $L^\infty$ theory of dense graph limits and its extension by Bollob\'as and Riordan to sparse graphs…

Combinatorics · Mathematics 2019-08-19 Christian Borgs , Jennifer T. Chayes , Henry Cohn , Yufei Zhao

In the on-line nearest-neighbour graph (ONG), each point after the first in a sequence of points in R^d is joined by an edge to its nearest-neighbour amongst those points that precede it in the sequence. We study the large-sample asymptotic…

Probability · Mathematics 2008-05-13 Mathew D. Penrose , Andrew R. Wade

Random geometric graphs consist of randomly distributed nodes (points), with pairs of nodes within a given mutual distance linked. In the usual model the distribution of nodes is uniform on a square, and in the limit of infinitely many…

Disordered Systems and Neural Networks · Physics 2018-09-27 Carl P. Dettmann

We develop efficient parameterized, with additive error, approximation algorithms for the (Connected) $r$-Domination problem and the (Connected) $p$-Center problem for unweighted and undirected graphs. Given a graph $G$, we show how to…

Data Structures and Algorithms · Computer Science 2017-06-26 Arne Leitert , Feodor F. Dragan

Hypergraphs are structures that can be decomposed or described; in other words they are recursively countable. Here, we get exact and asymptotic enumeration results on hypergraphs by means of exponential generating functions. The number of…

Discrete Mathematics · Computer Science 2008-06-20 Tsiriniaina Andriamampianina

In 1990 Bender, Canfield and McKay gave an asymptotic formula for the number of connected graphs on $[n]=\{1,2,\ldots,n\}$ with $m$ edges, whenever $n\to\infty$ and $n-1\le m=m(n)\le \binom{n}{2}$. We give an asymptotic formula for the…

Combinatorics · Mathematics 2018-11-05 Béla Bollobás , Oliver Riordan

Elek and Lippner (2010) showed that the convergence of a sequence of bounded-degree graphs implies the existence of a limit for the proportion of vertices covered by a maximum matching. We provide a characterization of the limiting…

Probability · Mathematics 2012-04-12 Charles Bordenave , Marc Lelarge , Justin Salez

This paper provides a necessary and sufficient condition for a random network with nodes Poissonly distributed on a unit square and a pair of nodes directly connected following a generic random connection model to be asymptotically almost…

Networking and Internet Architecture · Computer Science 2012-10-05 Guoqiang Mao , Brian Do Anderson

Let $G$ be a dense graph with good expansion properties and not too close to being bipartite. Let $\boldsymbol d$ be a graphical degree sequence. Under very weak conditions, we find the number of subgraphs of $G$ with degree sequence…

Combinatorics · Mathematics 2025-08-27 Mikhail Isaev , Brendan D. McKay

We develop a cluster expansion for the probability of full connectivity of high density random networks in confined geometries. In contrast to percolation phenomena at lower densities, boundary effects, which have previously been largely…

Disordered Systems and Neural Networks · Physics 2015-06-03 Justin Coon , Carl P. Dettmann , Orestis Georgiou